# AI Made Personal Projects Fun Again

## My recent experience building personal projects.

Over the last year or so, I’ve struggled to finish personal projects. I’d start something I was excited about, set my expectations way too high, and eventually give up when it started to feel like too much. Once I stopped trying to make every project perfect and something revolutionary, I actually started getting much more out of my personal projects.

**This month, I've built a simple stock screener.** It is a rather small project that does the following:

1. Scrapes for all publicly traded S&P 500 companies
2. Uses the Yfinance API to pull earnings data.
3. Runs multi-threaded calculations based on a set criteria.
4. Generates a CSV of all of the "good deals" in the market based on certain criteria, and pushes this to my Google Sheets account via the Google API.

I wanted to learn more about multithreading, the stock market, and the yfinance API. I had fun building the screener and looked forward to working on it every time I sat down.

## Personal projects are FUN now!

**That’s when it clicked for me:** If personal projects carry less weight on your resume, maybe that’s actually a good thing for people who genuinely enjoy the craft of programming.

Now when I build software at home, it is out of sheer curiousity and intrigue. Now that almost anyone can make impressive SWE projects, It has aleviated the pressure of every project having to make it to my resume.

**Now, I really am building things for myself.** And this shift has seriously lit a spark in my motivation to build in my free time.

## How to get the most out of personal projects in the AI age.

In 2026 (and the coming years after), I would advise students and newer programmers to build things they genuinely enjoy. And **do not avoid AI for research and learning**, but maybe avoid AI generated code until you have the capacity to write/read/debug the code yourself.

**If you are experienced in programming, there is no shame in using AI generated code in personal projects.** I'd recommend creating custom skills, agents, `.md` files and prompts that you can showcase when someone asks you how you built it (rather than "I just used Claude"). AI usage in itself is a skill that you can polish (and is only going to become more valuable).

**Focus on understanding your infrastructure.** Now that we can build faster, it gives us more time to understand how to deploy our applications. Nowadays it is more important than ever to understand things like Docker, Kubernetes, AWS, and basic networking.

## Where to shift your focus for resume-building?

**A polished demo alone tells a hiring manager much less than it used to.** AI makes it easier to build something that looks impressive, so choose a project that is unique and gives interviewers a reason to ask about it.

For example: the stock screener I mentioned earlier. I’d be perpared to talk about why I capped it at three worker threads, and how I cached the ticker list top prevent API rate-limiting. Those are decisions I can explain in an interview.

<mark>If you’re building something with your resume in mind, I’d pick a project that gives you a few decisions worth talking about. For example:</mark>

- **AI workflows.** Build custom skills, agents, or workflows for tasks you do regularly. Explain what you automated and how you checked that it worked.
- **Infrastructure.** Deploy a service and explain what you did to keep costs down, handle failures, or make it easier to operate.
- **Low-level programming.** Build something in C, C++, or Rust and walk through a decision you made about memory, concurrency, or performance.

## Conclusion

<mark>Have fun building stuff, and build things for yourself!!!!</mark>